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Record W2793828414 · doi:10.1002/cjce.23199

A Study on Thermodiffusion in Ternary Liquid Mixtures Using Enhanced Molecular Dynamics Algorithm with Experimental Validation

2018· article· en· W2793828414 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicField-Flow Fractionation Techniques
Canadian institutionsMcMaster UniversityToronto Metropolitan University
Fundersnot available
KeywordsTernary operationThermodynamicsAlgorithmMaterials scienceChemistryMathematicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

Abstract The objective of this paper is to study thermodiffusive flow in several ternary liquid mixtures of dodecane (nC12)‐1,2,3,4‐tetrahydronaphthalene (THN)‐isobutylbenzene (IBB) for four different compositions at normal pressure and temperature using our recently proposed modified heat exchange (mHEX) algorithm. Predictions from this algorithm are compared with the experimental data obtained in the reduced gravity environment. Comparisons have also been made with the standard heat exchange algorithm to show that the mHEX algorithm is significantly better in predicting the thermodiffusive separation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.226
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it